Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The presence of distributed generators with DC output power and the advancement in power electronics devices have motivated system planners and grid operators to move towards integration of DC microgrids into conventional AC grid. In this paper, we address the optimal power flow (OPF) problem in AC-DC networks. The goal of the AC-DC OPF problem is to jointly minimize the total electricity generation cost of the network and the cost of transferring active power from the AC grid to the DC microgrids. The optimization problem is subject to the power flow constraints, voltage magnitude limits, the limits of the network power lines, and the limits imposed by the power ratings of AC-DC power electronic converters. The formulated AC-DC OPF problem is shown to be nonlinear. We propose an approach to reformulate the AC-DC OPF problem as an equivalent traditional AC OPF problem. Due to the non-convexity of the AC OPF problem, we use convex relaxation techniques and transform the problem to a semidefinite program (SDP). We show that the relaxation gap is zero. That is the optimal solution of the non-convex and the transformed convex problems are equal. Simulation studies are performed on an IEEE 14-bus system connected to two 9-bus DC microgrids. We show that the sufficient condition for the zero relaxation gap is satisfied, and the proposed SDP approach enables us to find the global optimal solution efficiently.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it